51 to 75 of 180 Distributed Computing Jobs in London

Hands-on experience with foundational software engineering practices.Database Proficiency: Strong knowledge of SQL for querying and managing data.Scalability: Experience scaling computations using GPUs or distributed computing systems.ML Integration: Familiarity with exposing machine learning components through web services or wrappers (e.g., Flask in Python).Soft Skills: Strong communication ...

/agent frameworks; cloud AI platforms (Amazon Bedrock, Azure OpenAI/AI Foundry, Google Vertex AI); vector databases; containerization and orchestration (Docker, Kubernetes); distributed computing. Architecture Design – end‐to‐end design of Generative and Agentic AI architectures encompassing data preprocessing, model selection, RAG pipelines, agent orchestration, MCP‐based integration ...

security function, translating threat intelligence into real-time detections, coordinating incident response across multiple teams, and hunting for sophisticated attacks across GPU clusters and distributed training environments. If you're excited by the challenge of securing systems that are fundamentally different from anything you've protected before, this … identify AI-specific threats including prompt injection, model extraction, data poisoning, adversarial examples, and unauthorized access to training datasets or model weights across our distributed infrastructure Build automated response playbooks and orchestration workflows that contain threats without human intervention, creating self-healing security systems that reduce mean time ...

Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- PhD or a Master's degree and experience in engineering, technology, computer science, machine learning, robotics, operations research ...

Java, C++, Python or related language- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing- Experience in building machine learning models for business application- PhD, or a Master's degree and experience ...

Java, C++, Python or related language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Experience in building machine learning models for business application PhD, or a Master's degree and experience ...

signal computation, trade-decision-making and execution.Design, implement, and maintain the core systems and services to enable real time data ingestion, retrieval and distributed compute for both research and production.Oversee the ongoing operation of all components within the systems landscape to ensure resilience and detect defects as they arise.Preferred … Technical SkillsExceptional programming skills in both high-level and low-level languages (Python & C++ or similar).Familiarity with modern distributed computing platforms (specifically: docker, kubernetes, ceph, mongodb & kafka).Theoretical proficiency in numerical computing, online algorithms, data structures, networking, databases, and operating systems.Familiarity with typical quantitative research toolchains ...

financial services industry. We specialise in complex software engineering environments where performance, robustness and scalability are critical: real-time systems, low-latency architectures, distributed computing and high-throughput data processing. Joining MARGO means working in demanding Front Office and Trading IT environments, while benefiting from a human-sized … incident prevention Technical Environment Core Technologies C#/.NET (expert level) Concurrency and parallel programming Asynchronous and multithreaded models Memory management and performance profiling Distributed and event-driven architectures Windows and/or Linux production environments Performance monitoring and profiling tools Valued Technical Exposure Electronic trading or low-latency ...

Experience managing/mentoring/coaching high performance data teams A passion for writing high quality code and building lean processes Experience with distributed data processing Experience with monitoring, testing, and data quality Experience building robust pipelines from diverse sources e.g. parquet, SQL & no-SQL databases, API endpoints … would be helpful to have experience/expertise/knowledge in the following: Python AWS Spark & distributed computing dbt Terraform Data Warehousing (we use Databricks but experience with other platforms is fine) MLOps implementation (desirable but not required) Airflow (or other orchestration tooling) #J-18808-Ljbffr ...

desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver … stop you from applying.Why AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services ...

build and manage robust data pipelines that convert raw, diverse data sources (batch, streaming, real-time and unstructured) into reliable, analysis-ready datasets, using distributed computing techniques to process data at scale. Responsibilities: Design and build data ingestion pipelines and orchestration tooling. Develop database schemas and data models. ...

Need3+ years of experience in a data engineeringStrong proficiency in Python and RustHands-on experience with AWS cloud, Linux, and Docker.Expertise in distributed computing frameworks (Ray, Dask, or Apache Arrow).Strong analytical skills, with the ability to handle large-scale, high-frequency data.Solid understanding of ETL pipelines, data ...

ideal candidate has experience working with large datasets and distributed computing technologies. They relish working with large volumes of data, enjoy the challenge of highly complex technical contexts, and above all else are passionate about data and analytics. They are expert in data modelling, ETL design, and business ...

Business Intelligence Engineer, BAT, Data & Analytics Job ID: 10515285 | Amazon EU SARL (UK Branch) The ideal candidate has experience working with large datasets and distributed computing technologies. They relish working with large volumes of data, enjoy the challenge of highly complex technical contexts, and above all else ...

platform, applied to financial market data.Our stack includes modern C++ for throughput-critical ingestion and simulation, Python with C++ bindings for research tooling, and distributed computing on HPC clusters. Your work will span exchange-data ingestion, HPC orchestration, simulation, and research tooling.Trading experience is not required; we provide … market connectivity.GPU programming experience.Historical network/packet processing (telco, network appliances, packet-capture replay infrastructure).Deterministic simulation and replay systems (game engines, cell simulators, distributed-systems testing frameworks).Dev-productivity or platform-engineering for internal users (making other engineers or researchers faster and safer, at scale).What we evaluate ...

data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar)Proven experience building or maintaining machine learning systems in a distributed computing environmentProficiency developing in a Linux environment with attention to performance, correctness, and reproducibilityExceptional attention to detail, particularly when working with imperfect or heterogeneous … software engineeringPreferred QualificationsExperience with experiment management, model evaluation pipelines, or ML workflow orchestrationFamiliarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training)Experience with performance profiling and optimization of numerical or modeling codePrior exposure to financial data, time-series analysis, or quantitative research environments“Friends ...

data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar) Proven experience building or maintaining machine learning systems in a distributed computing environment Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility Exceptional attention to detail, particularly when working with imperfect … Qualifications Experience with experiment management, model evaluation pipelines, or ML workflow orchestration Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training) Experience with performance profiling and optimization of numerical or modeling code Prior exposure to financial data, time-series analysis, or quantitative research environments ...

Platform Engineer partners with the Analytics product engineering team to design, build and operate platform capabilities that enable our market leading high-performance, distributed computing products to run reliably, securely and efficiently at scale. This includes infrastructure automation, runtime orchestration, CI/CD enablement, observability and performance optimisation. … resilience in a regulated environment. Key accountabilities Define and execute the platform engineering strategy and roadmap aligned to analytics product needs. Design and operate distributed runtime environments including compute orchestration and workload scheduling. Implement Infrastructure as Code (IaC) and automated environment provisioning. Build and maintain CI/CD pipelines ...

applied to financial market data. Our stack includes modern C++ for throughput-critical ingestion and simulation, Python with C++ bindings for research tooling, and distributed computing on HPC clusters. Your work will span exchange-data ingestion, HPC orchestration, simulation, and research tooling. Trading experience is not required … programming experience. Historical network/packet processing (telco, network appliances, packet‐capture replay infrastructure). Deterministic simulation and replay systems (game engines, cell simulators, distributed‐systems testing frameworks). Dev‐productivity or platform‐engineering for internal users (making other engineers or researchers faster and safer, at scale). ...

enables quants, data scientists, and engineers to create, share, and run code at scale. Our multidisciplinary team are delivering notebook experiences with Jupyter & VSCode, distributed compute with Dask/Spark, and the runtime building blocks that power model development, pricing, and risk analytics across the organization. You’ll help ...

robust data pipelines to assist analysis of large datasets Develop infrastructure for trading services to convert research ideas into production Experience with large-scale distributed computing technologies Requirements Bachelor’s degree or higher in computer science or other quantitative discipline 3+ years of Python/C++ required. (Post ...

analytics Experience with signal pipelines, research platforms, backtesting systems, or live trading infrastructure Experience building monitoring tools, dashboards, or operational analytics platforms Familiarity with distributed computing, workflow orchestration, or large-scale data pipelines Experience using LLMs, coding agents, or AI tools to automate software development, testing, documentation ...

models with approaches like LoRA, QLoRA, DoRA; quantization and distillation. Familiarity with prompt optimization frameworks and building prompt pipelines and evaluation suites. Experience with distributed computing, data sharding, and performance optimization. Hands‐on experience with AWS services related to AI deployment and workflow orchestration. Why Join ...

teams to integrate pricing models and workflow enhancements within the ACE application. There will be exposure to a wide range of technological frameworks, including distributed computing architecture. Responsibilities Developing and maintaining the Counterparty Credit Risk applications, leveraging in-house Python and C++ model libraries. Supporting and improving ...

models with approaches like LoRA, QLoRA, DoRA; quantization and distillation. Familiarity with prompt optimization frameworks and building prompt pipelines and evaluation suites. Experience with distributed computing, data sharding, and performance optimization. Hands‐on experience with AWS services related to AI deployment and workflow orchestration. Why Join ...